Field of the Invention
This invention relates to an image processing method for document images, and in particular, it relates to a method for segmenting a document image based on pixels of 2D objects in the image.
Description of Related Art
A “document image” refers to a digital image representing a document which includes a substantial amount of text. For example, a document image may be generated by scanning a hard copy document, taking a photograph of a hard copy document, converting a text-based electronic document (e.g. a Word document) into an image format (e.g. PDF™), etc. Document image processing refers to various processing conducted for document images. One example of document image processing is optical character recognition (OCR), which aims to extract the textual content of the document. Another example of document image processing is document authentication, which aims to determine whether a target document image is the same as an original document image or whether it has been altered.
One step in document image processing is image segmentation, i.e. segmenting the document image into image segments that contain different types of contents, each segment containing only one type of content, such as text, tables, graphics, images, etc. Text may be further segmented into blocks of text such as paragraphs, etc. Many image segmentation methods have been described. For example, U.S. Pat. Appl. Pub. No. US 2003/0072487 describes a method for segmenting an image using the background. A low pass filter is applied on the image, and then the image is processed at low resolution by low resolution segmentation. Segmentation includes identification of the objects and the main background. This method can only be used to segment embedded images from text based on their different frequencies.
Some image segmentation methods first classify 2D objects in the document image into different types such as text, graphics, image, etc., and then segment the image based on the types of the objects. The processing of the second step is often complex and time-consuming.